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Multi-satellite Mission Planning Using a Self-Adaptive Multi-agent System

机译:自适应多主体系统的多卫星任务计划

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Mission planning for a constellation of Earth observation satellites is a complex problem raising significant technological challenges for tomorrow's space systems. The large numbers of customers requests and their dynamic introduction in the planning system result in a huge combinatorial search space with a potentially highly dynamical evolution requirements. The techniques used nowadays have several limitations, in particular, it is impossible to dynamically adapt the plan during its construction even for small modifications. Satellites of a constellation are planned in a chronological way instead of a more collective planning which can provide additional load balancing. In this paper, we propose to solve this difficult and highly dynamic problem using adaptive multi-agent systems, taking advantage from their self-adaptation and self-organization mechanisms. In the proposed system, the agents, through their local interactions, allow to dynamically reach a good solution, while ensuring a controlled distribution of tasks within the constellation of satellites. Finally, a comparison with a classical chronological greedy algorithm, commonly used in the spatial domain, highlights the advantages of the presented system.
机译:对地观测卫星群的任务计划是一个复杂的问题,对明天的太空系统提出了重大的技术挑战。大量的客户需求及其在计划系统中的动态介绍导致了巨大的组合搜索空间,并可能具有高度动态变化的需求。如今使用的技术有一些局限性,特别是,即使在进行微小修改的情况下,也无法在计划的构建过程中动态地调整计划。星座卫星是按时间顺序进行规划的,而不是可以提供额外负载平衡的更总体的规划。在本文中,我们建议利用自适应多主体系统的自适应和自组织机制来解决这一难题和高度动态的问题。在提出的系统中,代理通过它们的本地交互作用,可以动态地获得良好的解决方案,同时确保在卫星星座内可控地分配任务。最后,与通常在空间域中使用的经典时间贪婪算法进行比较,凸显了所提出系统的优势。

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